AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work proposes \method, an evaluation allocation framework that combines sparse search-time feedback with targeted final confirmation and achieves higher mean performance than full evaluation in most settings while using approximately half as many evaluation cells.
Results show that a fixed-weight, self-evolving harness can revise, recover, and accumulate verified approaches while producing structured trajectories for future supervised and reinforcement learning.
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